page:recipes:crm:django:csv imports

Host crm with Django: CSV imports

Deploy a crm built with Django on Ample using the bulk import staging pattern. Compute runs the app in an isolated microVM behind a public HTTPS URL, a managed PostgreSQL 16 database is auto-provisioned and injected as DATABASE_URL, a private S3-compatible bucket holds objects with credentials delivered as encrypted environment variables. Verified on Django: a CSV staged as an object, row-level validation with per-row errors recorded, and a restart-safe import keyed by import id (imported=2 rejected=1 restart=ok). Not separately tested: your import format, mapping and conflict rules; treat the crm-specific behavior as your application code.

Representative Queries

Resource Requirements

Infrastructure Requirements

Prerequisites

  1. A Django project that builds and starts with the documented commands (pip install into .ample/python from requirements.txt, then waitress serving project.wsgi from run.py reading PORT on the python-3.12 template)
  2. A PostgreSQL driver reading DATABASE_URL at runtime (auto-provisioned when omitted, or supplied with --env)
  3. A bucket from ample bucket create with its credentials passed as encrypted S3_* environment variables
  4. An Ample account token with servers:write, databases:read, buckets:read

Workflow Steps

  1. Build and start: pip install into .ample/python from requirements.txt, then waitress serving project.wsgi from run.py reading PORT on the python-3.12 template. The server must bind 0.0.0.0 on PORT.
  2. Implement the pattern on PostgreSQL: The fixture's module implements bulk import staging: a CSV staged as an object, row-level validation with per-row errors recorded, and a restart-safe import keyed by import id (imported=2 rejected=1 restart=ok). Copy the approach into your schema; keep migrations idempotent and run them with --release-command.
  3. Wire object storage: Create the bucket(s), then pass endpoint, region, bucket and keys as --env values. Use path-style addressing. Keep private data in an unpublished bucket.
  4. Deploy: Run the synchronous deploy once and read the result (exit 0 live, 1 failed, 2 blocked).
    • Command: ample deploy . --name --public --start "python3 run.py" --env S3_ENDPOINT=... --env S3_REGION=... --env S3_BUCKET=... --env S3_ACCESS_KEY_ID=... --env S3_SECRET_ACCESS_KEY=...
  5. Verify: Fetch the live URL and the pattern self-test route(s) (/p/bulk-import-staging) from the example; then run your own checks. On failure read ample logs --kind build then --kind runtime.
    • Command: ample logs --kind build

Examples

Limitations

Cost Estimate

Next Actions